Oncology/Hematology

Radiomic Model Associated with Tumor Microenvironment Predicts Immunotherapy Response and Prognosis in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma.

No robust biomarkers have been identified to predict the efficacy of programmed cell death protein ...

Patient acceptability of CITOBOT for cervical cancer screening: A mixed-method study.

This study assessed the acceptability of CITOBOT, a device for early cervical cancer screening in a ...

Establishing a miRNA panel for hepatocellular carcinoma screening through a multicenter study.

Most patients with hepatocellular carcinoma (HCC) are often diagnosed at advanced stages, limiting t...

MRI Radiomics and Automated Habitat Analysis Enhance Machine Learning Prediction of Bone Metastasis and High-Grade Gleason Scores in Prostate Cancer.

RATIONALE AND OBJECTIVES: To explore the value of machine learning models based on MRI radiomics and...

Ensemble-based Convolutional Neural Networks for brain tumor classification in MRI: Enhancing accuracy and interpretability using explainable AI.

BACKGROUND: Accurate and efficient classification of brain tumors, including gliomas, meningiomas, a...

A model developed by machine learning and principal component analysis for predicting bronchiolitis obliterans syndrome after allogeneic HSCT in a Chinese population with hematologic malignancies.

Bronchiolitis obliterans syndrome (BOS) is a severe pulmonary complication following allogeneic hema...

[Incidental pulmonary nodules on CT imaging: what to do?].

Incidental pulmonary nodules are very frequently found on CT imaging and may represent (early stage)...

CellMemory: hierarchical interpretation of out-of-distribution cells using bottlenecked transformer.

Machine learning methods, especially Transformer architectures, have been widely employed in single-...

Palmitoylation regulators drive the progression of clear cell renal cell carcinoma through Inhibition of cuproptosis: insights into the role of ZDHHC18.

BACKGROUND: Protein palmitoylation is a reversible post-translational modification that increases pr...

Development of the treatment prediction model in the artificial intelligence in depression - medication enhancement study.

We introduce an artificial intelligence model to personalize treatment in major depression, which wa...

Machine Learning Model for Predicting Sertraline-like Activities and Its Impact on Cancer Chemosensitization.

Selective serotonin reuptake inhibitors (SSRIs) like sertraline are crucial in treating depression a...

Machine learning-based detoxification enzymes-related genes prognosis model in breast cancer: immune landscape and clinical significance.

BACKGROUND: Breast cancer is one of the most common malignant tumors, threatening women's health and...

Clinical benefits of deep learning-assisted ultrasound in predicting lymph node metastasis in pancreatic cancer patients.

AIM: This study aimed to develop and validate a deep learning radiomics nomogram (DLRN) derived from...

Enabling Early Identification of Malignant Vertebral Compression Fractures via 2.5D Convolutional Neural Network Model with CT Image Analysis.

STUDY DESIGN: This study employed a retrospective data analysis approach combined with model develop...

Hyperspectral Imaging Combined With Deep Learning for Precision Grading of Clear Cell Renal Cell Carcinoma.

This study presents an integrated approach combining hyperspectral imaging (HSI) and deep learning f...

Axial Skeletal Assessment in Osteoporosis Using Radiofrequency Echographic Multi-spectrometry: Diagnostic Performance, Clinical Utility, and Future Directions.

Osteoporosis, a prevalent skeletal disorder, necessitates accurate and accessible diagnostic tools f...

The impact of artificial intelligence on the endoscopic assessment of inflammatory bowel disease-related neoplasia.

Inflammatory bowel disease (IBD) is a group of chronic inflammatory conditions of the gastrointestin...

PCPAm - A dataset of histopathological images of penile cancer for classification tasks.

Penile cancer has an incidence strongly linked to sociocultural factors, being more common in underd...

Deep learning dosiomics in grade 4 radiation-induced lymphopenia prediction in radiotherapy for esophageal cancer: a multi-center study.

PURPOSE: To investigate the feasibility and accuracy of using deep learning and dosiomics features, ...

Correction: Machine learning for cardio-oncology: predicting global longitudinal strain from conventional echocardiographic measurements in cancer patients.

Accurate de novo design of high-affinity protein-binding macrocycles using deep learning.

Developing macrocyclic binders to therapeutic proteins typically relies on large-scale screening met...